Processing complex aggregate queries over data streams

Recent years have witnessed an increasing interest in designing algorithms for querying and analyzing streaming data (i.e., data that is seen only once in a fixed order) with only limited memory. Providing (perhaps approximate) answers to queries over such continuous data streams is a crucial requirement for many application environments; examples include large telecom and IP network installations where performance data from different parts of the network needs to be continuously collected and analyzed. In this paper, we consider the problem of approximately answering general aggregate SQL queries over continuous data streams with limited memory. Our method relies on randomizing techniques that compute small "sketch" summaries of the streams that can then be used to provide approximate answers to aggregate queries with provable guarantees on the approximation error. We also demonstrate how existing statistical information on the base data (e.g., histograms) can be used in th...

• Type: Conference
• Year: 2002
• Where: SIGMOD
• Authors: Alin Dobra, Minos N. Garofalakis, Johannes Gehrke, Rajeev Rastogi
• Keywords: Aggregate Sql Queries, Continuous Data Streams, Database, SIGMOD 2002, Synthetic Data Streams